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Quantum Computation for Big Information Processing
Published in Neeraj Kumar, N. Gayathri, Md. Arafatur Rahman, B. Balamurugan, Blockchain, Big Data and Machine Learning, 2020
Tawseef Ayoub Shaikh, Rashid Ali
Because of the unavailability of quantum computers and necessary hardware for its implementation, lack of proper tools and simulation environments for carrying out the quantum simulation, quantum computing is still in its infancy stage posing a hot challenge in the information processing. But a lot of progress is going on in this field and in time, it may become the treasure house for big data analytics. Since modern data sets generated from different sources, possessing vast formats like text, image, sensor readings, and streaming data. Likewise, quantum computing has its basic units as quantum (photons), so it can be worth of use to remove this heterogeneity or variety problem in the big data, as the data in it is being analyzed at the electronic level. Once the quantum computer hardware will be ready in the next couple of years, quantum computing will be the hottest topic for tackling down the big data analytics problems.
Quantum Information Processes
Published in Thiruselvan Subramanian, Archana Dhyani, Adarsh Kumar, Sukhpal Singh Gill, Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network, 2023
B.S. Tewari, P. Mandal, Prashant Rawat
There are many interesting quantum algorithms, which can handle a range of practical problems. These problems are solvable more efficiently using quantum algorithms, in contrast to classical computing algorithms. The quantum algorithms are broadly divided into three categories. The first is a group of algorithms based on quantum analogues of the Fourier transform. The examples are Deutsch’s algorithm and Shor’s algorithm. The second and third classes of algorithms are quantum search algorithms and quantum simulation algorithms, respectively, in which a quantum computer is used to search data and simulate a quantum system, respectively. The first class of algorithms have been reported accompanying a giant development in quantum circuits and computations.
The Future of Electronics
Published in John D. Cressler, Silicon Earth, 2017
For example, integer factorization (the decomposition of a composite number into a product of smaller integers) is computationally intractable with a classical digital computer for very large integers, if they are the product of prime numbers (e.g., the product of two 300-digit prime numbers). By comparison, a quantum computer could efficiently solve this problem using something called Shor’s algorithm (don’t ask) to find its factors. This ability would allow a quantum computer to quickly decrypt many of the cryptographic systems in use today. Yikes! In particular, most of the popular public key ciphers in use today are based on this difficulty digital computers have of factoring large integers. Such key ciphers are used to protect secure webpages, encrypt e-mail, and essentially lock-down many other types of data from prying eyes. Quantum computers can break those encryptions, with massive ramifications for electronic privacy and security. On a global scale. Read: this is a big deal. Besides factorization, quantum computers offer substantial speed-up over classical digital computers for several other problems, including the simulation of quantum physical processes from chemistry and solid-state physics, and database searching. Since, by definition, chemistry and nanotechnology rely on the detailed understanding of quantum systems, and such systems are impossible to simulate in an efficient manner classically, quantum simulation is likely to be one of the most important applications of quantum computing. Quantum simulation could also be used to simulate the behavior of atoms and particles under unusual conditions, such as the reactions inside a particle collider (think LHC at CERN). Read: quantum computers can do LOTS of cool things. That is, if we can actually build them!
Theoretical approaches for doubly-excited Rydberg states in quasi-two-electron systems: two-electron dynamics far away from the nucleus
Published in Molecular Physics, 2021
Rydberg-based quantum computing and quantum simulation with alkaline-earth metal atoms relies on high Rydberg-detection fidelities which, in some experiments, depend on the excitation dipole moments to core-excited Rydberg states and on their autoionisation rates [27]. Such quantities can be calculated using CI-ECS and their knowledge is desirable to select, in current and future experiments, the most suitable core-excited Rydberg states. The production of core-excited Rydberg states that are metastable against autoionisation is actively pursued in the context of Rydberg-atom trapping and manipulation [26,28,29], and typically relies on increasing the orbital-angular-momentum quantum number l of the Rydberg electron. The l-dependence of the autoionisation rates of core-excited Rydberg states is not well understood, and a theoretical investigation of the subject using CI-ECS is under way.
Sideband cooling of small ion Coulomb crystals in a Penning trap
Published in Journal of Modern Optics, 2018
G. Stutter, P. Hrmo, V. Jarlaud, M. K. Joshi, J. F. Goodwin, R. C. Thompson
In quantum information experiments, the common modes of motion of ICCs provide a convenient mechanism for transmitting information between ions [12]. Radio-frequency, linear Paul traps are prevalent in this kind of work, typically using one-dimensional crystals that align along the radio frequency null of the trap [13]. Such a system with three ions in a line has been used to simulate the frustration that occurs when three spins arearranged in a triangle configuration [14]. In contrast, planar ICCs in a Penning trap naturally form in a triangular lattice, which provides a suitable platform for quantum simulation of frustrated systems [15], without the need for highly specialised trap designs [16,17].
Quantum technology a tool for sequencing of the ratio DSS/DNA modifications for the development of new DNA-binding proteins
Published in Egyptian Journal of Basic and Applied Sciences, 2022
Adamu Yunusa Ugya, Kamel Meguellati
Quantum technology is a new field of physics and engineering that is based on quantum physics principles. Quantum computing, quantum sensors, quantum cryptography, quantum simulation, quantum metrology, and quantum imaging are all examples of quantum technologies that use quantum mechanics properties, particularly quantum entanglement, quantum superposition, and quantum tunneling [85]. Any science concerned with systems that display noticeable quantum-mechanical effects, where waves have particle qualities and particles behave like waves, is referred to as quantum physics. Quantum mechanics has applications in both explaining natural events and developing technology that rely on quantum effects, such as integrated circuits and lasers [86]. Quantum mechanics is also crucial for understanding how covalent bonds connect individual atoms to form molecules. Quantum chemistry is the application of quantum mechanics to chemistry. Quantum mechanics may also demonstrate which molecules are energetically favorable to which others and the magnitudes of the energy involved in ionic and covalent bonding processes [86]. The algebraic determination of the hydrogen spectrum by [87] and the treatment of diatomic molecules by [88] were the earliest applications of quantum mechanics to physical systems. Modern technology operates on a scale where quantum effects are significant in many ways. Quantum chemistry, quantum optics, quantum computing, superconducting magnets, light-emitting diodes, the optical amplifier and laser, the transistor and semiconductors such as the microprocessor, and medical and research imaging such as magnetic resonance imaging and electron microscopy are all important applications of quantum theory. Many biological and physical phenomena, most notably the macromolecule DNA, have explanations based on the nature of chemical bonds. Multiple governments have established quantum technology exploration programs since 2010, including the UK National Quantum Technologies Programme [89], which created four quantum ‘hubs’, the Singapore Center for Quantum Technologies, and QuTech, a Dutch center to develop a topological quantum computer [90]. The European Union launched the Quantum Technology Flagship in 2016, a €1 billion, ten-year megaproject comparable to the European Future and Emerging Technologies Flagship initiatives. The National Quantum Initiative Act, passed in December 2018, allocates a $1 billion annual budget for quantum research in the United States. Large corporations have made multiple investments in quantum technology in the private sector. Google’s collaboration with the John Martinis group at UCSB, various relationships with D-wave Systems, a Canadian quantum computing business, and investment by many UK corporations in the UK quantum technologies initiative are just a few examples [91].